Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and rob...
In this paper, we present a method of object classification within the context of Visual Surveillance. Our goal is the classification of tracked objects into one of the two classe...
John-Paul Renno, Dimitrios Makris, Graeme A. Jones
Visual tracking, in essence, deals with non-stationary data streams that change over time. While most existing algorithms are able to track objects well in controlled environments,...
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...